[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"extension-skill-lijigang-ljg-qa-zh-CN":3,"guides-for-lijigang-ljg-qa":265,"similar-k1768dnvxxvyptnpx4vpcebjdx867zsy":266},{"_creationTime":4,"_id":5,"children":6,"community":7,"display":9,"evaluation":19,"identity":185,"isFallback":190,"parentExtension":191,"providers":241,"relations":245,"repo":246,"workflow":264},1778053348890.7847,"k1768dnvxxvyptnpx4vpcebjdx867zsy",[],{"reviewCount":8},0,{"description":10,"installMethods":11,"name":12,"sourceUrl":13,"tags":14},"信息提问机。给一篇文章/论文/书，把核心观点抽成 Q-A 对——Question 切要害，不教科书；Answer 简洁清晰，有形式化收口，逻辑链完整。读者顺 Q 链走过，每个 A 砸下一枚钉子，复现作者整套推理。Use when user says '问答', 'Q&A', 'QA', '提问', '抽取问题', '/ljg-qa', or shares an article/paper/book and asks for Q-A extraction. Triggers when the user wants ideas extracted not as a summary but as a sequence of incisive questions with answered. NOT FOR FAQ generation, glossary creation, or comprehension quizzes — this is intellectual scaffolding, not study aids.",{},"信息提问机","https://github.com/lijigang/ljg-skills/tree/HEAD/skills/ljg-qa",[15,16,17,18],"qa","summarization","information-extraction","documentation",{"_creationTime":20,"_id":21,"extensionId":5,"locale":22,"result":23,"trustSignals":174,"workflow":183},1778053415028.5667,"kn75xh2b9hcne8fmp18v3han1n867xc5","en",{"checks":24,"evaluatedAt":164,"extensionSummary":165,"promptVersionExtension":166,"promptVersionScoring":167,"rationale":168,"score":169,"summary":170,"tags":171,"targetMarket":172,"tier":173},[25,30,33,36,40,43,48,52,54,57,62,66,69,73,76,79,82,85,88,91,94,98,102,106,110,113,116,119,123,126,129,132,135,138,142,145,148,151,154,157,161],{"category":26,"check":27,"severity":28,"summary":29},"Practical Utility","Problem relevance","pass","The description clearly states the problem: extracting core ideas from text into Q-A pairs where questions are incisive and answers are concise and complete, serving as intellectual scaffolding.",{"category":26,"check":31,"severity":28,"summary":32},"Unique selling proposition","The skill offers a unique value proposition by focusing on extracting the 'argumentative skeleton' and reasoning path of an author, rather than a simple summary or FAQ. The structured Q-A format with specific answer requirements (conclusion, formalization, steps, boundaries) differentiates it from standard summarization tools.",{"category":26,"check":34,"severity":28,"summary":35},"Production readiness","The skill appears production-ready, with a clear workflow defined in `Workflows/Extract.md` covering content acquisition, argument extraction, Q-A generation, and output formatting, including fallback mechanisms for different input types.",{"category":37,"check":38,"severity":28,"summary":39},"Scope","Single responsibility principle","The extension has a single, well-defined responsibility: extracting core ideas from text into a structured Q-A chain, avoiding scope creep into unrelated domains.",{"category":37,"check":41,"severity":28,"summary":42},"Description quality","The displayed description is accurate, concise, and clearly communicates the extension's purpose, unique value, and intended use cases, including explicit non-goals.",{"category":44,"check":45,"severity":46,"summary":47},"Invocation","Scoped tools","not_applicable","This skill does not expose distinct tools; its functionality is invoked via a single command with different input types.",{"category":49,"check":50,"severity":46,"summary":51},"Documentation","Configuration & parameter reference","The skill does not appear to have configurable parameters beyond input type, making this check not applicable.",{"category":37,"check":53,"severity":46,"summary":47},"Tool naming",{"category":37,"check":55,"severity":28,"summary":56},"Minimal I/O surface","The skill takes clearly defined inputs (URL, file, text) and produces a structured output in org-mode format, with specific naming conventions.",{"category":58,"check":59,"severity":60,"summary":61},"License","License usability","critical","No license information is provided in the repository, and no explicit license file or SPDX identifier is present. This makes redistribution and use legally ambiguous.",{"category":63,"check":64,"severity":60,"summary":65},"Maintenance","Commit recency","There are no commits on the default branch for this repository, indicating it is likely unmaintained and poses a significant risk.",{"category":63,"check":67,"severity":46,"summary":68},"Dependency Management","The skill appears to be self-contained or relies on standard Claude/LLM capabilities, with no explicit third-party dependencies that require management.",{"category":70,"check":71,"severity":46,"summary":72},"Security","Secret Management","The skill does not appear to handle any secrets.",{"category":70,"check":74,"severity":28,"summary":75},"Injection","The skill's workflow appears to treat fetched content as data and does not instruct the LLM to execute instructions from it, aligning with security best practices.",{"category":70,"check":77,"severity":28,"summary":78},"Transitive Supply-Chain Grenades","The skill does not fetch remote content as executable instructions or include untrusted code, mitigating transitive supply-chain risks.",{"category":70,"check":80,"severity":28,"summary":81},"Sandbox Isolation","The skill operates by fetching and processing content, and its output is directed to specified file paths without attempting to modify files outside its intended scope or use absolute paths.",{"category":70,"check":83,"severity":28,"summary":84},"Sandbox escape primitives","No detached-process spawns or deny-retry loops were detected in the provided script.",{"category":70,"check":86,"severity":28,"summary":87},"Data Exfiltration","The skill's primary function is content processing and output generation; there are no indications of it reading or submitting confidential data to third parties.",{"category":70,"check":89,"severity":28,"summary":90},"Hidden Text Tricks","The bundled files do not contain any hidden text tricks, control characters, or invisible Unicode sequences designed to steer the model deceptively.",{"category":70,"check":92,"severity":28,"summary":93},"Opaque code execution","The provided scripts are in plain text and do not contain obfuscated code, base64 payloads, or runtime fetched scripts.",{"category":95,"check":96,"severity":28,"summary":97},"Portability","Structural Assumption","The skill uses standard output paths and relative file handling, avoiding assumptions about specific user project structures or OS-specific paths.",{"category":99,"check":100,"severity":46,"summary":101},"Trust","Issues Attention","No issues data is available for this repository.",{"category":103,"check":104,"severity":60,"summary":105},"Versioning","Release Management","There is no version information available in the manifest files, no GitHub release tags, and no CHANGELOG. The installation instructions likely default to the main branch, making version pinning impossible.",{"category":107,"check":108,"severity":28,"summary":109},"Code Execution","Validation","The skill defines clear input handling based on type (URL, file, text) and specifies output formats and naming conventions, indicating implicit validation through structured processing.",{"category":70,"check":111,"severity":46,"summary":112},"Unguarded Destructive Operations","The skill's operations involve content fetching and processing, not destructive actions like file deletion or system changes.",{"category":107,"check":114,"severity":28,"summary":115},"Error Handling","The workflow defines distinct steps for different input types and includes a fallback for direct text input, suggesting a structured approach to handling variations and potential errors.",{"category":107,"check":117,"severity":46,"summary":118},"Logging","The skill's primary function is content processing and output generation, and it does not perform destructive actions or sensitive outbound calls that would necessitate a local audit log.",{"category":120,"check":121,"severity":28,"summary":122},"Compliance","GDPR","The skill processes text content and does not appear to handle personal data directly, nor does it submit data to third parties.",{"category":120,"check":124,"severity":28,"summary":125},"Target market","The skill is language-agnostic and processes text content, with no apparent regional or jurisdictional restrictions; targetMarket is global.",{"category":95,"check":127,"severity":28,"summary":128},"Runtime stability","The skill relies on standard web fetching and file operations, with clear instructions for different input types, suggesting good cross-platform compatibility.",{"category":44,"check":130,"severity":28,"summary":131},"Precise Purpose","The description clearly defines the skill's purpose (extracting core ideas into Q-A chains), its specific triggers ('问答', 'Q&A', article/paper/book sharing), and its non-goals (not FAQ, glossary, or comprehension quizzes).",{"category":44,"check":133,"severity":28,"summary":134},"Concise Frontmatter","The frontmatter is concise and effectively summarizes the core capability, including trigger phrases and specific non-goals.",{"category":49,"check":136,"severity":28,"summary":137},"Concise Body","The main `SKILL.md` file is concise, and detailed procedural information is delegated to `Workflows/Extract.md` and design patterns to `References/QuestionDesign.md`, following progressive disclosure.",{"category":139,"check":140,"severity":28,"summary":141},"Context","Progressive Disclosure","Detailed procedural steps are in `Workflows/Extract.md` and design patterns are in `References/QuestionDesign.md`, linked from the main `SKILL.md`.",{"category":139,"check":143,"severity":46,"summary":144},"Forked exploration","The skill's workflow involves content extraction and Q-A generation, not deep code review or exploration that would benefit from 'context: fork'.",{"category":26,"check":146,"severity":28,"summary":147},"Usage examples","Sufficient examples are provided for different input types (URL, PDF, text), clearly outlining the invocation and expected outcome.",{"category":26,"check":149,"severity":28,"summary":150},"Edge cases","The skill handles different input types (URL, file, text) and provides specific guidance for PDF processing (pages parameter), indicating consideration for variations in input.",{"category":107,"check":152,"severity":28,"summary":153},"Tool Fallback","The skill defines fallbacks for different input types (e.g., direct text input skips fetching), ensuring robustness.",{"category":95,"check":155,"severity":28,"summary":156},"Stack assumptions","The skill's workflow uses standard tools like `WebFetch`, `Read`, and `curl` for notifications, which are common and generally available, with no exotic language runtimes assumed.",{"category":158,"check":159,"severity":28,"summary":160},"Safety","Halt on unexpected state","The workflow outlines distinct steps for different input types and provides guidance for processing, implying a structured halt if unexpected states occur.",{"category":95,"check":162,"severity":28,"summary":163},"Cross-skill coupling","The skill appears self-contained and does not implicitly rely on other skills being loaded. It uses standard tools for its operations.",1778053389767,"This skill processes articles, papers, or books to generate a series of incisive questions and concise, structured answers. It aims to reconstruct the author's reasoning path, distinguishing itself from summaries or FAQs by acting as intellectual scaffolding. The output is formatted in org-mode.","2.0.0","3.4.0","The extension is flagged due to critical findings in License Usability and Commit Recency, indicating potential legal ambiguity and a high risk of unmaintained code. Additionally, the lack of versioning information is a critical issue for production readiness.",45,"This skill extracts core ideas from text into a structured Q-A chain, focusing on authorial reasoning and argument.",[15,16,17,18],"global","flagged",{"codeQuality":175,"collectedAt":176,"documentation":177,"maintenance":179,"security":180,"testCoverage":182},{},1778053377046,{"descriptionLength":178,"readmeSize":8},466,{},{"hasNpmPackage":181,"smitheryVerified":181},false,{"hasCi":181,"hasTests":181},{"updatedAt":184},1778053415028,{"githubOwner":186,"githubRepo":187,"locale":22,"slug":188,"type":189},"lijigang","ljg-skills","ljg-qa","skill",true,{"_creationTime":192,"_id":193,"community":194,"display":195,"identity":208,"parentExtension":210,"providers":234,"relations":239,"workflow":240},1778053348890.7798,"k1704g81mbxzdxt81951f8s6g1866ry3",{"reviewCount":8},{"description":196,"installMethods":197,"name":198,"sourceUrl":199,"tags":200},"LJG's personal Claude Code skills collection",{},"LJG Skills Collection","https://github.com/lijigang/ljg-skills",[201,202,203,204,18,205,206,207],"skills","content-creation","writing","research","visualization","productivity","academic",{"githubOwner":186,"githubRepo":187,"locale":22,"slug":187,"type":209},"plugin",{"_creationTime":211,"_id":212,"community":213,"display":214,"identity":218,"providers":220,"relations":229,"workflow":231},1778053348890.7793,"k17axkces4ykqysd5mgcmajr89867sm1",{"reviewCount":8},{"description":215,"installMethods":216,"name":198,"sourceUrl":199,"tags":217},"Personal Claude Code skills collection for paper reading, content casting, and writing workflows",{},[201,202,204,203,206],{"githubOwner":186,"githubRepo":187,"locale":22,"slug":187,"type":219},"marketplace",{"extract":221,"llm":227},{"commitSha":222,"license":223,"marketplace":224},"d2d6a0313baaeee789d00aa5c3841d4622147f23","MIT",{"name":187,"pluginCount":225,"version":226},1,"1.17.15",{"promptVersionExtension":166,"promptVersionScoring":167,"score":228,"targetMarket":172,"tier":173},88,{"repoId":230},"kd71hhp7w2dcgt37rznesw08cx864k8w",{"anyEnrichmentAt":232,"extractAt":233,"githubAt":232,"llmAt":184,"updatedAt":184},1778053349620,1778053348890,{"extract":235,"llm":236},{"commitSha":222,"license":223},{"promptVersionExtension":166,"promptVersionScoring":167,"score":237,"targetMarket":172,"tier":238},90,"verified",{"parentExtensionId":212,"repoId":230},{"anyEnrichmentAt":232,"extractAt":233,"githubAt":232,"llmAt":184,"updatedAt":184},{"extract":242,"llm":244},{"commitSha":222,"license":243},"n/a",{"promptVersionExtension":166,"promptVersionScoring":167,"score":169,"targetMarket":172,"tier":173},{"parentExtensionId":193,"repoId":230},{"_creationTime":247,"_id":230,"identity":248,"providers":249,"workflow":261},1777995558409.893,{"githubOwner":186,"githubRepo":187,"sourceUrl":199},{"discover":250,"github":253},{"sources":251},[252],"skills-sh",{"closedIssues90d":254,"forks":255,"openIssues90d":256,"pushedAt":257,"readmeSize":258,"stars":259,"topics":260},5,458,2,1777870782000,4594,3935,[],{"discoverAt":262,"extractAt":263,"githubAt":263,"updatedAt":263},1777995558409,1778053350730,{"anyEnrichmentAt":232,"extractAt":233,"githubAt":232,"llmAt":184,"updatedAt":184},[],[267,292,319,340,369,398],{"_creationTime":268,"_id":269,"community":270,"display":271,"identity":278,"providers":281,"relations":286,"workflow":288},1778053622473.661,"k17bjq5477qz3ff878vxz3gc4d8667dn",{"reviewCount":8},{"description":272,"installMethods":273,"name":274,"sourceUrl":275,"tags":276},"Create effective summaries by matching summarization type to purpose, audience, and context. Use when asked to summarize, create TLDR, condense content, or create executive summaries. Keywords: summary, TLDR, condense, executive summary, abstract.",{},"Summarization","https://github.com/jwynia/agent-skills/tree/HEAD/skills/general/writing/revision/summarization",[203,16,18,277],"text-processing",{"githubOwner":279,"githubRepo":280,"locale":22,"slug":16,"type":189},"jwynia","agent-skills",{"extract":282,"llm":284},{"commitSha":283,"license":223},"e02ec7e226a6e4f8419fd3b88a1d8e472d421b32",{"promptVersionExtension":166,"promptVersionScoring":167,"score":285,"targetMarket":172,"tier":238},98,{"repoId":287},"kd7efn3mprpa8rd8vm5hw5ebzx864fph",{"anyEnrichmentAt":289,"extractAt":290,"githubAt":289,"llmAt":291,"updatedAt":291},1778053625386,1778053622473,1778054012696,{"_creationTime":293,"_id":294,"community":295,"display":296,"identity":305,"providers":308,"relations":313,"workflow":315},1778053148350.4265,"k171agyyd8nv26rt447dvhy0998669wm",{"reviewCount":8},{"description":297,"installMethods":298,"name":299,"sourceUrl":300,"tags":301},"Answer questions about PDF content, summarize, and extract information",{},"Chat with PDF","https://github.com/claude-office-skills/skills/tree/HEAD/chat-with-pdf",[302,15,303,16,304,18],"pdf","extraction","mcp",{"githubOwner":306,"githubRepo":201,"locale":22,"slug":307,"type":189},"claude-office-skills","chat-with-pdf",{"extract":309,"llm":311},{"commitSha":310,"license":223},"9c4c7d5cd2813a8936bf2c9fdb174ea883b85a11",{"promptVersionExtension":166,"promptVersionScoring":167,"score":312,"targetMarket":172,"tier":238},95,{"repoId":314},"kd7fw7xbj58qc2z8whrrjptbed8659db",{"anyEnrichmentAt":316,"extractAt":317,"githubAt":316,"llmAt":318,"updatedAt":318},1778053151766,1778053148350,1778053561145,{"_creationTime":320,"_id":321,"community":322,"display":323,"identity":332,"providers":334,"relations":338,"workflow":339},1778053622473.6594,"k171jc4epkmqq2y76n42e3eg0s866rf8",{"reviewCount":8},{"description":324,"installMethods":325,"name":326,"sourceUrl":327,"tags":328},"Systematically identify what's missing in non-fiction writing—both blind spots (inherent limitations) and blank spots (gaps that could be addressed). Use before finalizing non-fiction or when feedback feels incomplete.",{},"Blind Spot Detective","https://github.com/jwynia/agent-skills/tree/HEAD/skills/general/writing/analysis/blind-spot-detective",[203,329,330,331,18],"analysis","non-fiction","diagnostic",{"githubOwner":279,"githubRepo":280,"locale":22,"slug":333,"type":189},"blind-spot-detective",{"extract":335,"llm":336},{"commitSha":283,"license":223},{"promptVersionExtension":166,"promptVersionScoring":167,"score":337,"targetMarket":172,"tier":238},99,{"repoId":287},{"anyEnrichmentAt":289,"extractAt":290,"githubAt":289,"llmAt":291,"updatedAt":291},{"_creationTime":341,"_id":342,"community":343,"display":344,"identity":355,"providers":359,"relations":363,"workflow":365},1778054663200.0623,"k1787qemz1vae1jy4xsx7c2zyn867dwd",{"reviewCount":8},{"description":345,"installMethods":346,"name":347,"sourceUrl":348,"tags":349},"Maps the full customer journey from first touch to advocacy. Generates a comprehensive customer-journey.md with all stages, touchpoints, emotions, pain points, opportunities, Mermaid diagrams, and metrics. Use when mapping customer experience, designing onboarding flows, identifying churn risks, or optimizing conversion funnels.",{},"Customer Journey Mapper","https://github.com/onewave-ai/claude-skills/tree/HEAD/customer-journey-mapper",[350,351,352,353,18,354],"customer-experience","journey-mapping","strategy","marketing","reporting",{"githubOwner":356,"githubRepo":357,"locale":22,"slug":358,"type":189},"onewave-ai","claude-skills","customer-journey-mapper",{"extract":360,"llm":362},{"commitSha":361,"license":223},"eb3d80be32b6cafcf0d5df1c1b8a95df75838271",{"promptVersionExtension":166,"promptVersionScoring":167,"score":285,"targetMarket":172,"tier":238},{"repoId":364},"kd71e43dj0b7ak5e55pyshxp4n864t6p",{"anyEnrichmentAt":366,"extractAt":367,"githubAt":366,"llmAt":368,"updatedAt":368},1778054667983,1778054663200,1778055270278,{"_creationTime":370,"_id":371,"community":372,"display":373,"identity":385,"providers":388,"relations":392,"workflow":394},1778054812528.7205,"k179w7m3n2zkvrbhmmwn1stces86799q",{"reviewCount":8},{"description":374,"installMethods":375,"name":376,"sourceUrl":377,"tags":378},"3D web graphics with Three.js (WebGL/WebGPU). Capabilities: scenes, cameras, geometries, materials, lights, animations, model loading (GLTF/FBX), PBR materials, shadows, post-processing (bloom, SSAO, SSR), custom shaders, instancing, LOD, physics, VR/XR. Actions: create, build, animate, render 3D scenes/models. Keywords: Three.js, WebGL, WebGPU, 3D graphics, scene, camera, geometry, material, light, animation, GLTF, FBX, OrbitControls, PBR, shadow mapping, post-processing, bloom, SSAO, shader, instancing, LOD, WebXR, VR, AR, product configurator, data visualization, architectural walkthrough, interactive 3D, canvas. Use when: creating 3D visualizations, building WebGL/WebGPU apps, loading 3D models, adding animations, implementing VR/XR, creating interactive graphics, building product configurators.",{},"3D Graphics with Three.js","https://github.com/samhvw8/dot-claude/tree/HEAD/skills/3d-graphics",[379,380,381,382,18,383,384],"three-js","webgl","webgpu","3d-graphics","learning","examples",{"githubOwner":386,"githubRepo":387,"locale":22,"slug":382,"type":189},"samhvw8","dot-claude",{"extract":389,"llm":391},{"commitSha":390,"license":223},"28c76162116d2eedab131c0e1548fdc76a2999f7",{"promptVersionExtension":166,"promptVersionScoring":167,"score":285,"targetMarket":172,"tier":238},{"repoId":393},"kd79ad9dpqazy79y2s6rvajgjn865xek",{"anyEnrichmentAt":395,"extractAt":396,"githubAt":395,"llmAt":397,"updatedAt":397},1778054813688,1778054812528,1778054896678,{"_creationTime":399,"_id":400,"community":401,"display":402,"identity":411,"providers":414,"relations":418,"workflow":420},1778054564989.5369,"k1767w6z2kv4rgf7gryn1saw6x867n0n",{"reviewCount":8},{"description":403,"installMethods":404,"name":405,"sourceUrl":406,"tags":407},"Refactor CLAUDE.md files to follow progressive disclosure principles. Use when CLAUDE.md is too long or disorganized.",{},"ReClaude","https://github.com/brianlovin/claude-config/tree/HEAD/skills/reclaude",[18,408,409,410],"refactoring","markdown","claude-config",{"githubOwner":412,"githubRepo":410,"locale":22,"slug":413,"type":189},"brianlovin","reclaude",{"extract":415,"llm":417},{"commitSha":416,"license":46},"1a9819ebf3fee811150fc76cbe177ea4e5f747ff",{"promptVersionExtension":166,"promptVersionScoring":167,"score":285,"targetMarket":172,"tier":238},{"repoId":419},"kd7c7ftew8fsa52skn0fm3rfvd864fmn",{"anyEnrichmentAt":421,"extractAt":422,"githubAt":421,"llmAt":423,"updatedAt":423},1778054565711,1778054564989,1778054628464]